{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GY3I5S5MMCFLYDDJZX6WGJTI6N","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"49380168b19c180617bd93ea124fd80bb901637529bc33677857f190aa1da6cf","cross_cats_sorted":["cs.AI","cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T16:56:45Z","title_canon_sha256":"21a0e41a64c6f38e1d2c4ec588fa4bcc2dba58960574d8acda25e3289bd4462e"},"schema_version":"1.0","source":{"id":"2406.17838","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.17838","created_at":"2026-07-05T08:36:50Z"},{"alias_kind":"arxiv_version","alias_value":"2406.17838v1","created_at":"2026-07-05T08:36:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.17838","created_at":"2026-07-05T08:36:50Z"},{"alias_kind":"pith_short_12","alias_value":"GY3I5S5MMCFL","created_at":"2026-07-05T08:36:50Z"},{"alias_kind":"pith_short_16","alias_value":"GY3I5S5MMCFLYDDJ","created_at":"2026-07-05T08:36:50Z"},{"alias_kind":"pith_short_8","alias_value":"GY3I5S5M","created_at":"2026-07-05T08:36:50Z"}],"graph_snapshots":[{"event_id":"sha256:c995f231977cf89295895bbbc036a24d141f7e757966365a8a400223c1033492","target":"graph","created_at":"2026-07-05T08:36:50Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2406.17838/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The emergence of large-scale pre-trained models has heightened their application in various downstream tasks, yet deployment is a challenge in environments with limited computational resources. Knowledge distillation has emerged as a solution in such scenarios, whereby knowledge from large teacher models is transferred into smaller student' models, but this is a non-trivial process that traditionally requires technical expertise in AI/ML. To address these challenges, this paper presents InFiConD, a novel framework that leverages visual concepts to implement the knowledge distillation process a","authors_text":"Chris Bryan, Jinbin Huang, Liang Gou, Liu Ren, WenBin He","cross_cats":["cs.AI","cs.HC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T16:56:45Z","title":"InFiConD: Interactive No-code Fine-tuning with Concept-based Knowledge Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.17838","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b3e0e83d6eb32bb3419d43e3ae7b101181a19982eba7fb00b9faa7ce67c906c9","target":"record","created_at":"2026-07-05T08:36:50Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"49380168b19c180617bd93ea124fd80bb901637529bc33677857f190aa1da6cf","cross_cats_sorted":["cs.AI","cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T16:56:45Z","title_canon_sha256":"21a0e41a64c6f38e1d2c4ec588fa4bcc2dba58960574d8acda25e3289bd4462e"},"schema_version":"1.0","source":{"id":"2406.17838","kind":"arxiv","version":1}},"canonical_sha256":"36368ecbac608abc0c69cdfd632668f369721f8a8de11cd82f34169aa01b48ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36368ecbac608abc0c69cdfd632668f369721f8a8de11cd82f34169aa01b48ce","first_computed_at":"2026-07-05T08:36:50.864581Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:36:50.864581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qnLKaHWYNdG3MgakzugfO8J6fr9j7itPvTHhlxoZkzAYBTQ77t1KDaMpfJRBBi0cCUpAhUXCox/oS847fAzqAg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:36:50.865051Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.17838","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3e0e83d6eb32bb3419d43e3ae7b101181a19982eba7fb00b9faa7ce67c906c9","sha256:c995f231977cf89295895bbbc036a24d141f7e757966365a8a400223c1033492"],"state_sha256":"cc765ffbfc306f8780fcf973086c8a0d23e6f89276f85bb5e489f53caf1e2fc1"}